Abstract
 Identification of Economic Clusters Using ArcGIS Spatial Statistics Track: Business GIS Author(s): Joseph Frizado, Bruce Smith, Michael Carroll Geographic proximity (co-location) is necessary for potential clustering activity. Therefore, the identification of potential cluster areas is the necessary first phase in a cluster economic development policy. Measures of spatial autocorrelation can used to delineate such clusters. Using the example of the transportation equipment industry in the United States, this research evaluates the application of spatial statistics in the identification of potential cluster areas. Alternative methods of creating the spatial weights matrix integral to such methodologies will be addressed with respect to the distribution of spatial unit dimensions and geometries, as well as the relationship between spatial weights matrices and cluster theory. Joseph Frizado Bowling Green State University Geology 190 Overman Hall, BGSU Bowling Green , OH 43402 US Phone: 419 372 7202 E-mail: frizado@bgsu.edu Bruce Smith Bowling Green State University Center for Regional Development & Department of Geography 305 Hanna Hall Bowling Green State University Bowling Green , OH 43403 US Phone: 419-372-7829 E-mail: bsmith@bgnet.bgsu.edu Michael Carroll Bowling Green State University Center for Regional Development & Department of Economics 109 South Hall Bowling Green State University Bowling Green , OH 43403 US Phone: 419 372 8710 E-mail: mcarrol@bgnet.bgsu.edu |
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